One of the most perplexing problems in the field of automatic image processing is the proper orientation of related but not necessarily identical frames of image data, also referred to in the pattern recognition literature as the correspondence problem. It encompasses problems such as the registration of two images, the problem of stereo projection, the problem of ranging by the use of two images, and many others.
It is known that useful information can be extracted by registering two frames of image data matrices, i.e., by superimposing them and comparing the differences between the pixels of the two frames. Such a technique is useful, for example, to detect motion of an object that has occurred between the times that the two image frames were taken. Assuming perfect registration between the two frames, by subtracting the values of the corresponding pixels the stationary features will be removed while leaving pixels associated with the moving object since its location will be different in the two frames.
Unfortunately, the registration of two images is no easy task. The task is somewhat simpler when there is a priori knowledge about the characteristics of the scene being investigated. If, for example, a reference map has been made beforehand, then it is much easier to project the image onto the reference map since the orientation and spatial location of the landmarks are fixed in the latter. General purpose computers have been employed with some success using parametric correspondence and chamfer matching techniques for image matching. See, e.g., Barrow et al, "Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching", Proceedings of the Fifth International Conference on Artificial Intelligence, 1977. Other techniques are disclosed in U.S. Pat. No. 3,905,045.
This image correspondence problem becomes particularly acute when there is little, if any, a priori knowledge of the scene under investigation. In the field of FLIR (forward looking infrared) imagery, image data is obtained from an infrared scanner mounted on an airplane surveying a large territory. It is highly desirable, in some applications, to be able to automatically detect the motion of an object within the gathered image data. However, there is generally little a priori knowledge of the particular terrain from which the image data is derived. Further aggravating the situation is the fact that the orientation and scale between successive frames of image data can be quite different due to the motion of the aircraft. Consequently, it is extremely burdensome and difficult to obtain useful information under such circumstances.